ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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Concordance of B‐ and T‐cell responses to SARS‐CoV‐2 infection, irrespective of symptoms suggestive of COVID‐19
This article has 15 authors:Reviewed by ScreenIT
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At-home Testing and Risk Factors for Acquisition of SARS-CoV-2 Infection in a Major US Metropolitan Area
This article has 15 authors:Reviewed by ScreenIT
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SARS-CoV-2 Omicron Variant, Lineage BA.1, Is Associated with Lower Viral Load in Nasopharyngeal Samples Compared to Delta Variant
This article has 11 authors:Reviewed by ScreenIT
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Private Equity Acquisition in Ophthalmology and Optometry: A Time Series Analysis of the Pre-COVID, COVID Pre-Vaccine, and COVID Post-Vaccine Eras
This article has 7 authors:Reviewed by ScreenIT
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Development and optimization of a high‐throughput screening assay for in vitro anti‐SARS‐CoV‐2 activity: Evaluation of 5676 Phase 1 Passed Structures
This article has 14 authors:Reviewed by ScreenIT
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Doxycycline for the prevention of progression of COVID-19 to severe disease requiring intensive care unit (ICU) admission: A randomized, controlled, open-label, parallel group trial (DOXPREVENT.ICU)
This article has 12 authors:Reviewed by ScreenIT
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Longitudinal Aging Study Amsterdam COVID-19 exposure index: a cross-sectional analysis of the impact of the pandemic on daily functioning of older adults
This article has 12 authors:Reviewed by ScreenIT
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Occurrence of Relative Bradycardia and Relative Tachycardia in Individuals Diagnosed With COVID-19
This article has 3 authors:Reviewed by ScreenIT
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BNT162b2, mRNA-1273, and Sputnik V Vaccines Induce Comparable Immune Responses on a Par With Severe Course of COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Mental health in a diverse sample of healthcare workers during the COVID-19 pandemic: cross-sectional analysis of the UK-REACH study
This article has 26 authors:Reviewed by ScreenIT